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update the peak throughput plotter to show the difference of smart and allnodes too

master
Constantin Fürst 1 year ago
parent
commit
1fca956a0a
  1. 31
      benchmarks/benchmark-plotters/plot-perf-peakthroughput.py

31
benchmarks/benchmark-plotters/plot-perf-peakthroughput.py

@ -7,6 +7,8 @@ import matplotlib.pyplot as plt
from common import calc_throughput
folder_path = "benchmark-results/"
runid = "Run ID"
x_label = "Destination Node"
y_label = "Source Node"
@ -18,6 +20,8 @@ title_allnodes = \
title_smartnodes = \
"""Copy Throughput in GiB/s tested for 1GiB Elements\n
Using Cross-Copy for Intersocket and all 4 Chiplets of Socket for Intrasocket"""
title_difference = \
"""Gain in Copy Throughput in GiB/s of All-DSA vs. Smart Assignment"""
description_smartnodes = \
"""Copy Throughput in GiB/s tested for 1GiB Elements\n
@ -68,15 +72,23 @@ def process_file_to_dataset(file_path, src_node, dst_node):
return
def plot_heatmap(table,title,node_config):
plt.figure(figsize=(8, 6))
sns.heatmap(table, annot=True, cmap="YlGn", fmt=".0f")
plt.title(title)
plt.savefig(os.path.join(folder_path, f"plot-perf-{node_config}-throughput.png"), bbox_inches='tight')
plt.show()
# loops over all possible configuration combinations and calls
# process_file_to_dataset for them in order to build a dataframe
# which is then displayed and saved
def main(node_config,title):
folder_path = "benchmark-results/"
for src_node in range(16):
for dst_node in range(16):
size = "512mib" if src_node == dst_node and src_node >= 8 else "1gib"
size = "512mib" if node_config == "allnodes" and src_node == dst_node and src_node >= 8 else "1gib"
file = os.path.join(folder_path, f"copy-n{src_node}ton{dst_node}-{size}-{node_config}-1e.json")
process_file_to_dataset(file, src_node, dst_node)
@ -85,15 +97,14 @@ def main(node_config,title):
data.clear()
df.set_index(index, inplace=True)
data_pivot = df.pivot_table(index=y_label, columns=x_label, values=v_label)
plt.figure(figsize=(8, 6))
sns.heatmap(data_pivot, annot=True, cmap="rocket_r", fmt=".0f")
plot_heatmap(data_pivot, title, node_config)
plt.title(title)
plt.savefig(os.path.join(folder_path, f"plot-perf-{node_config}-throughput.png"), bbox_inches='tight')
plt.show()
return data_pivot
if __name__ == "__main__":
main("allnodes", title_allnodes)
main("smart", title_smartnodes)
dall = main("allnodes", title_allnodes)
dsmart = main("smart", title_smartnodes)
ddiff = dall - dsmart
plot_heatmap(ddiff,title_difference,"diff")
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